L'objectif de cette thèse est de réunir les deux approches suivantes qui existent actuellement pour étudier une foule: ou bien à temps fixé on s'intéresse à la distribution spatiale des individus, ou bien on suit un seul individu à la fois au cours du temps. On se propose de construire des processus spatio-temporels, qui, comme leur nom l'indique, permettraient de rendre compte du caractère aléatoire des usages d'une foule dans un réseau de télécommunication, à la fois du point de vue spatial (modèles de route) et du point de vue temporel (déplacements sur ces routes, usages qui varient au cours de ces déplacements…). Une fois ces processus construits de manière rigoureuse, on étudie leur comportement d'une manière fine. Nous développons trois modèles différents qui chacun mènent à des formules analytiques fermées, ce qui permet de les utiliser d'une manière très confortable à des fins de dimensionnement. / This thesis consists in joining two approaches that currently exist when one wants to study crowds phenomena: either taking a snapshot by freezing time to study the spatial repartition of the individuals, or following one given individual over time.We build space-time processes that let us model random phenomena in a crowd, being on a spatial level (roads models) or a time level (movings on these roads, space-dependent behaviors…). Once we have built them in a rigorous manner, we study their properties, which let us obtain analytical closed formulas that can be widely used for dimensioning purposes.

The capacity of a cellular system is limited by two different phenomena, namely multipath fading and multiple access interference (MAI). A Two Dimensional (2-D) receiver combats both of these by processing the signal both in the spatial and temporal domain. An ideal 2-D receiver would perform joint space-time processing, but at the price of high computational complexity. In this dissertation we investigate computationally simpler technique termed as a Beamformer-Rake. In a Beamformer-Rake, the output of a beamformer is fed into a succeeding temporal processor to take advantage of both the beamformer and Rake receiver. Wireless service providers throughout the world are working to introduce the third generation (3G) cellular service that will provide higher data rates and better spectral efficiency. Wideband CDMA (WCDMA) has been widely accepted as one of the air interfaces for 3G. A Beamformer-Rake receiver can be an effective solution to provide the receivers enhanced capabilities needed to achieve the required performance of a WCDMA system. This dissertation investigates different Beamformer-Rake receiver structures suitable for the WCDMA system and compares their performance under different operating conditions. This work develops Beamformer-Rake receivers for WCDMA uplink that employ Eigen-Beamforming techniques based on the Maximum Signal to Noise Ratio (MSNR) and Maximum Signal to Interference and Noise Ratio (MSINR) criteria. Both the structures employ Maximal Ratio Combining (MRC) to exploit temporal diversity. MSNR based Eigen-Beamforming leads to a Simple Eigenvalue problem (SE). This work investigates several algorithms that can be employed to solve the SE and compare the algorithms in terms of their computational complexity and their performance. MSINR based Eigen-Beamforming results in a Generalized Eigenvalue problem (GE). The dissertation describes several techniques to form the GE and algorithms to solve it. We propose a new low-complexity algorithm, termed as the Adaptive Matrix Inversion (AMI), to solve the GE. We compare the performance of the AMI to other existing algorithms. Comparison between different techniques to form the GE is also compared. The MSINR based beamforming is demonstrated to be superior to the MSNR based beamforming in the presence of strong interference. There are Pilot Symbol Assisted (PSA) beamforming techniques that exploit the Minimum Mean Squared Error (MMSE) criterion. We compare the MSINR based Beamformer-Rake with the same that utilizes Direct Matrix Inversion (DMI) to perform MMSE based beamforming in terms of Bit Error Rate (BER). In a wireless system where the number of co-channel interferers is larger than the number of elements of a practical antenna array, we can not perform explicit null-steering. As a result the advantage of beamforming is partially lost. In this scenario it is better to attain diversity gain at the cost of spatial aliasing. We demonstrate this with the aid of simulation. Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier technique that has recently received considerable attention for high speed wireless communication. OFDM has been accepted as the standard for Digital Audio Broadcast (DAB) and Digital Video Broadcast (DVB) in Europe. It has also been established as one of the modulation formats for the IEEE 802.11a wireless LAN standard. OFDM has emerged as one of the primary candidates for the Fourth Generation (4G) wireless communication systems and high speed ad hoc wireless networks. We propose a simple pilot symbol assisted frequency domain beamforming technique for OFDM receiver and demonstrate the concept of sub-band beamforming. Vector channel models measured with the MPRG Viper test-bed is also employed to investigate the performance of the beamforming scheme. / Ph. D.

In todays society, a growing number of users are demanding more sophisticated services from wireless communication devices. In order to meet these rising demands, it has been proposed to increase the capacity of the wireless channel by using more than one antenna at the transmitter and receiver, thereby creating multiple-input multiple-output (MIMO) channels. Using MIMO communication techniques is a promising way to improve wireless communication technology because in a rich-scattering environment the capacity increases linearly with the number of antennas. However, increasing the number of transmit antennas also increases the complexity of detection at an exponential rate. So while MIMO channels have the potential to greatly increase the capacity of wireless communication systems, they also force a greater computational burden on the receiver. Even suboptimal MIMO detectors that have relatively low complexity, have been shown to achieve unprecedented high spectral efficiency. However, their performance is far inferior to the optimal MIMO detector, meaning they require more transmit power. The fact that the optimal MIMO detector is an impractical solution due to its prohibitive complexity, leaves a performance gap between detectors that require reasonable complexity and the optimal detector. The objective of this research is to bridge this gap and provide new solutions for managing the inherent performance-complexity trade-off in MIMO detection. The optimally-ordered decision-feedback (BODF) detector is a standard low-complexity detector. The contributions of this thesis can be regarded as ways to either improve its performance or reduce its complexity - or both. We propose a novel algorithm to implement the BODF detector based on noise-prediction. This algorithm is more computationally efficient than previously reported implementations of the BODF detector. Another benefit of this algorithm is that it can be used to easily upgrade an existing linear detector into a BODF detector. We propose the partial decision-feedback detector as a strategy to achieve nearly the same performance as the BODF detector, while requiring nearly the same complexity as the linear detector. We propose the family of Chase detectors that allow the receiver to trade performance for reduced complexity. By adapting some simple parameters, a Chase detector may achieve near-ML performance or have near-minimal complexity. We also propose two new detection strategies that belong to the family of Chase detectors called the B-Chase and S-Chase detectors. Both of these detectors can achieve near-optimal performance with less complexity than existing detectors. Finally, we propose the double-sorted lattice-reduction algorithm that achieves near-optimal performance with near-BODF complexity when combined with the decision-feedback detector.